Pandas 无法将输入转换为时间戳错误
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Pandas cannot convert input to timestamp error
提问by ajay
I have two variables in the data set beginning date (format datetime64[ns]) and end date(format datetime64[ns]). I'm using following code to get the dates between beginning date and end date.
我在数据集开始日期（格式 datetime64[ns]）和结束日期（格式 datetime64[ns]）中有两个变量。我正在使用以下代码来获取开始日期和结束日期之间的日期。
pd.date_range(start = data['beginning_date'], end = data['end_date'], freq = 'D')
but it's throwing following error.
但它抛出以下错误。
cannot convert input to timestamp
why I'm getting above error. I tried changing as below, but it doesn't work.
为什么我遇到上述错误。我尝试如下更改，但它不起作用。
pd.date_range(start = data['beginning_date'], end = data['end_date'], freq = 'D').astype('datetime')
and also i want each day as separate record, for example: beginning_date = 01APR2015 and end_date = 30APR2015, i want each day as separate record as below.
而且我希望每一天都作为单独的记录，例如： begin_date = 01APR2015 和 end_date = 30APR2015，我希望每一天都作为单独的记录，如下所示。
01APR2015
02APR2015 etc
How can I get it as a separate record?
我怎样才能把它作为一个单独的记录？
Thanks in Advance.
提前致谢。
回答by MaxU
Assuming you have the following DF:
假设您有以下 DF：
In [30]: df
Out[30]:
beginning_date end_date
0 2013-12-22 2014-01-01
1 2009-12-14 2009-12-28
2 2010-12-31 2011-01-11
I guess you tried to use seriesinstead of scalarvalues when calling pd.date_range()method:
我猜您在调用方法时尝试使用系列而不是标量值pd.date_range()：
In [31]: pd.date_range(df.beginning_date, df.end_date)
...
skipped
...
TypeError: Cannot convert input to Timestamp
So try this instead:
所以试试这个：
In [32]: pd.date_range(df.beginning_date.min(), df.end_date.max())
Out[32]:
DatetimeIndex(['2009-12-14', '2009-12-15', '2009-12-16', '2009-12-17', '2009-12-18', '2009-12-19', '2009-12-20', '2009-12-21', '2009-12-22',
'2009-12-23',
...
'2013-12-23', '2013-12-24', '2013-12-25', '2013-12-26', '2013-12-27', '2013-12-28', '2013-12-29', '2013-12-30', '2013-12-31',
'2014-01-01'],
dtype='datetime64[ns]', length=1480, freq='D')
回答by Tian Wolf
Would you please help to format the input firstly, then the convert would works.
请您先帮助格式化输入，然后转换才能工作。
pd.date_range(start = '30-APR-2015', end = '05-MAY-2015', freq = 'D')
And the output would be
输出将是
DatetimeIndex(['2015-04-30', '2015-05-01', '2015-05-02', '2015-05-03',
'2015-05-04', '2015-05-05'],
dtype='datetime64[ns]', freq='D')
回答by Alexander
Если кто придет сюда с этой проблемой из 2к20, то решение - применение lambda
Если кто придет сюда с этой проблемой из 2к20, то решение - применение lambda
If anyone comes here with this problem from 2k20, the solution is to use lambda...
如果有人从 2k20 遇到这个问题，解决方案是使用 lambda ...
f = lambda x: len(pd.date_range(start=x[0],end=x[1],freq='M'))
f = lambda x: len(pd.date_range(start=x[0],end=x[1],freq='M'))
df_clear['difference'] = df_clear[['start_month','finish_month']].apply(f, axis=1)
df_clear['difference'] = df_clear[['start_month','finish_month']].apply(f,axis=1)
